code: def transform(self, X, column):
      if len(self._uniq_values) == 2:
          X[column + "_" + str(self._uniq_values[1])] = (
              X[column] == self._uniq_values[1]
          ).astype(int)
      else:
          for v in self._uniq_values:
              X[column + "_" + str(v)] = (X[column] == v).astype(int)
  
      X.drop(column, axis=1, inplace=True)
      return X
  
file_path: mljar-supervised/supervised/preprocessing/label_binarizer.py
imports: import json
  import numpy
label_desc: Use image node_id 3 for calling the LabelBinarizer obj's underlying member method code with example usage: obj.transform(X, column) and returns: X